问题描述
某些遗传算法框架,例如 http://www.aforgenet.com/需要很多参数,例如突变率,人口规模等
Some Genetic Algorithm frameworks, such as http://www.aforgenet.com/ requires many parameters, such as mutation rate, population size, etc
对于这些参数有通用的最佳数字吗?我认为这取决于问题(健身功能延迟,突变延迟,重组延迟,进化速率等).我最初的想法是使用GA来配置另一个GA.
There is universal best numbers for such parameters? I believe that it depends on the problem (fitness function delay, mutation delay, recombination delay, evolution rate, etc). My first thought was to use a GA to configure another GA.
还有更好的主意吗?
推荐答案
有一次,我编写了一种遗传算法,将这些值包括在要变异的值中,基本上就像您说的那样,使用GA进行自我配置.效果出奇的好,尤其是因为我发现在计算过程中更改这些值是有益的.
The one time I programmed a genetic algorithm I included those values in the values to mutate, basically like you said using a GA to configure itself. It worked surprisingly well, especially since I've found it to be beneficial for those values to change over the course of it's computation.
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